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Agent Skill · 研究检索

runstr-fitness(跑步健身)

runstr-fitness 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

runstr-fitness 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 2,983。

总安装 51,041周安装 2,085GitHub Stars 公开资料未说明下载 16,346核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:runstr-fitness(跑步健身)
来源仓库:https://github.com/thewildhustle/runstr-fitness
安装命令:
openclaw skills install runstr-fitness
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install runstr-fitness

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

让您的 AI 代理能够访问您来自 RUNSTR 的健康和健身数据。从 Nostr 获取锻炼、习惯、日记条目、心情、步数等。当用户询问他们的锻炼情况、健身历史、健康习惯、情绪跟踪或想要基于真实数据的人工智能健身指导时使用。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install runstr-fitness;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

runstr-fitness 怎么安装?

在终端执行 openclaw skills install runstr-fitness。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

runstr-fitness 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

runstr-fitness 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

runstr-fitness 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

runstr-fitness 用的人多吗?

公开数据是累计安装 51,041 次,近一周安装 2,085 次,下载 16,346 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

runstr-fitness 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
runstr-fitness

跑步健身 · 本页

51,041—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
runstr-fitness
description
Give your AI agent access to your health and fitness data from RUNSTR. Fetches workouts, habits, journal entries, mood, steps, and more from Nostr. Use when the user asks about their workouts, fitness history, health habits, mood tracking, or wants AI fitness coaching based on real data.
metadata
{"openclaw":{"emoji":"\�\�","requires":{"bins":["nak"]},"install":[{"id":"go","kind":"go","package":"github.com/fiatjaf/nak@latest","bins":["nak"],"label":"Install nak via Go"}]}}

RUNSTR Fitness Skill

Give your AI agent access to your real health and fitness data. RUNSTR is a free fitness app that tracks workouts, habits, journal entries, mood, and steps — and stores encrypted backups on the Nostr protocol. This skill lets your bot read that data so it can help with fitness coaching, habit accountability, mood tracking, and health insights.

What your bot gets access to:

  • Workout history (running, walking, cycling, hiking, strength, yoga, etc.)
  • Daily habits and streaks (quit smoking, daily meditation, etc.)
  • Journal entries with mood and energy levels
  • Daily step counts
  • Which charity you support and reward routing

Setup: Getting Your Data to Your Bot

If you're already a RUNSTR user with backups enabled, skip to step 3.

1. Download RUNSTR (if you haven't)

  • iOS: Search "RUNSTR" on the App Store
  • Android: Available on Zapstore or direct APK
  • GitHub: https://github.com/RUNSTR (open source)

RUNSTR is free. You earn Bitcoin (sats) for working out.

2. Use the App

  • Create or import a Nostr identity (the app generates one for you)
  • Track workouts, log habits, write journal entries
  • Go to Settings > Backup and tap Backup to Nostr

This encrypts all your fitness data and publishes it to Nostr relays. Only you (with your private key) can read it.

3. Give Your Bot Your nsec

Your nsec is your Nostr private key. Find it in RUNSTR under Settings > Keys (or your Nostr key manager).

Tell your bot: "Here's my RUNSTR nsec: nsec1..."

Your bot uses the nsec to decrypt your encrypted fitness backup from Nostr. The nsec is never stored, logged, or transmitted — it's used only for the decryption step in your current session.

Why nsec and not npub? Your fitness data is encrypted. The public key (npub) can only see old public workout posts (if any). The private key (nsec) is needed to decrypt your habits, journals, mood, steps, and current workout history.

Privacy note: If you want a dedicated identity just for fitness data, create a new Nostr account in RUNSTR. Your fitness nsec doesn't have to be your main Nostr identity.

4. Keep Your Backup Fresh

Your bot sees whatever was in your last backup. After a week of new workouts, go to Settings > Backup in RUNSTR and tap backup again to sync the latest data to Nostr.


For the Agent: How to Fetch RUNSTR Data

Everything below is instructions for the AI agent, not the user.

Prerequisites

nak (Nostr Army Knife) must be installed:

go install github.com/fiatjaf/nak@latest

Relays

Always query these four relays (RUNSTR defaults):

wss://relay.damus.io wss://relay.primal.net wss://nos.lol wss://relay.nostr.band

Step 1: Decode the nsec

hex_sk=$(nak decode nsec1...)
hex_pk=$(nak key public $hex_sk)

Step 2: Fetch Profile (Kind 0)

nak req -k 0 -a $hex_pk -l 1 \
  wss://relay.damus.io wss://nos.lol | \
  jq -r '.content | fromjson | {name, about, lud16, picture}'

Step 3: Fetch Encrypted Backup (Kind 30078)

This is the primary data source.

nak req -k 30078 -a $hex_pk -t d=runstr-workout-backup -l 1 \
  wss://relay.damus.io wss://relay.primal.net wss://nos.lol wss://relay.nostr.band

If no backup found: Tell the user: "No backup found on Nostr. Open RUNSTR on your phone, go to Settings > Backup, and create one. Then try again."

If backup found but exportedAt is old: Warn the user that their backup is stale and recent data may be missing. Suggest they re-backup in the app.

Decrypt the Backup

The backup is NIP-44 self-encrypted and gzip-compressed.

Method 1: Using nak

content=$(nak req -k 30078 -a $hex_pk -t d=runstr-workout-backup -l 1 \
  wss://relay.damus.io wss://nos.lol | jq -r '.content')

# Decrypt (NIP-44 self-decryption: user to own pubkey)
decrypted=$(echo "$content" | nak encrypt --sec $hex_sk $hex_pk --decrypt)

# Decompress (check for ["compression", "gzip"] tag first)
echo "$decrypted" | base64 -d | gunzip | jq .

Method 2: Node.js fallback

// /tmp/decrypt-runstr.mjs — run with: node /tmp/decrypt-runstr.mjs <hex_sk> '<content>'
import { gunzipSync } from 'zlib';
import NDK, { NDKPrivateKeySigner } from '@nostr-dev-kit/ndk';

const signer = new NDKPrivateKeySigner(process.argv[2]);
const user = await signer.user();
const decrypted = await signer.decrypt(user, process.argv[3]);

try {
  console.log(gunzipSync(Buffer.from(decrypted, 'base64')).toString());
} catch {
  console.log(decrypted);
}

Backup Payload Structure

{
  "version": 1,
  "exportedAt": "2025-01-15T10:30:00Z",
  "appVersion": "1.6.5",
  "workouts": [
    {
      "id": "uuid",
      "type": "running",
      "startTime": "2025-01-15T07:00:00Z",
      "endTime": "2025-01-15T07:35:00Z",
      "duration": 2100,
      "distance": 5200,
      "calories": 312
    }
  ],
  "habits": [
    {
      "id": "id",
      "name": "No Smoking",
      "type": "abstinence",
      "currentStreak": 45,
      "longestStreak": 45,
      "checkIns": ["2025-01-15", "2025-01-14"]
    }
  ],
  "journal": [
    {
      "id": "uuid",
      "date": "2025-01-15",
      "content": "Great morning run today.",
      "mood": "great",
      "energy": 4,
      "tags": ["morning", "outdoors"]
    }
  ],
  "stepHistory": [
    { "date": "2025-01-15", "steps": 12450, "source": "healthkit" }
  ],
  "preferences": {
    "unitSystem": "imperial",
    "selectedCharity": "hrf"
  }
}

Field reference:

  • workouts[].type: running, walking, cycling, hiking, strength, meditation, yoga, diet, swimming, rowing
  • workouts[].duration: seconds
  • workouts[].distance: meters
  • habits[].type: "abstinence" (quitting something) or "positive" (building something)
  • journal[].mood: great, good, neutral, low, bad
  • journal[].energy: 1-5 scale
  • stepHistory[].source: healthkit, health_connect, native

Step 4: Check for Legacy Public Workouts (Kind 1301)

Older users may have public workout events. Always check:

nak req -k 1301 -a $hex_pk -l 50 \
  wss://relay.damus.io wss://relay.primal.net wss://nos.lol wss://relay.nostr.band

If found, parse tags array:

TagExample
exercise["exercise", "running"]
distance["distance", "5.2", "km"]
duration["duration", "00:30:45"]
calories["calories", "312"]
avg_pace["avg_pace", "05:39", "min/km"]
steps["steps", "8432"]
team["team", "hrf"]

Merge with backup data. Deduplicate by matching workout start times or IDs.

Step 5: Analyze and Present

Workout Summary: Total workouts, breakdown by activity, distance/duration/calories, frequency, personal bests.

Trends: Frequency changes, pace improvement, gaps, active days of week.

Habits: Current streaks, longest streaks, consistency rate.

Journal & Mood: Mood trend, energy averages, workout-mood correlation.

Steps: Daily average, weekly totals, trends.

Charity: Which team/charity, reward routing (user vs charity).

Step 6: Store Health Summary in Memory

Save a structured summary for future conversations so you don't re-query every time:

# Health & Fitness Summary
Last updated: YYYY-MM-DD
Source: RUNSTR (Nostr encrypted backup)
User: <name or npub>

## Recent Activity (Last 30 Days)
- Total workouts: X
- Running: X workouts, Y km, avg pace Z/km
- Walking: X workouts, Y km
- Cycling: X workouts, Y km

## Frequency
- X workouts/week avg
- Most active: [weekday]

## Habits
- [Habit]: X day streak

## Mood & Energy
- Avg mood: [level], Avg energy: X/5

## Steps
- Avg: X,XXX/day

## Insights
- [Patterns and observations]

Coaching Mode

Once you have data, you can:

  • Recommend workouts based on history and goals
  • Suggest rest days based on training load
  • Check in on habit streaks
  • Correlate mood with activity
  • Track goals ("run 20 km this week")
  • Remind based on usual workout schedule

Troubleshooting

ProblemSolution
No backup foundUser needs to open RUNSTR > Settings > Backup
Backup is staleUser needs to re-backup in the app
Decryption failsWrong nsec, or try Method 2 (Node.js)
nak not installedgo install github.com/fiatjaf/nak@latest
No Go installedUse Method 2 (Node.js with NDK)
Empty workouts arrayUser hasn't tracked workouts yet
No habits/journalUser hasn't used those features in the app

About RUNSTR

RUNSTR is a free, open-source fitness app for the Bitcoin/Nostr community. Track workouts, earn Bitcoin (sats) for exercising, support charities, and join fitness competitions. Your data is yours — stored on your device and backed up encrypted to Nostr.

  • Website: https://runstr.app
  • GitHub: https://github.com/RUNSTR
  • Rewards: 50 sats per daily workout via Lightning address
  • PPQ.AI credits: Earn AI credits for working out

平台分布

OpenClaw

82.17%
按下载量换算13,432

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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